A Bayesian approach for identification of ice Ih, ice Ic, high density, and low density liquid water with a torsional order parameter

Research output: Contribution to journalArticle

Abstract

An order parameter is proposed to classify the local structures of liquid and solid water. The order parameter, which is calculated from the O-O-O-O dihedral angles, can distinguish ice Ih, ice Ic, high density, and low density liquid water. Three coloring schemes are proposed to visualize each of the coexisting phases in a system using the order parameter on the basis of Bayesian decision theory. The schemes are applied to a molecular dynamics trajectory in which ice nucleation occurs following spontaneous liquid-liquid separation in the deeply supercooled region as a demonstration.

Original languageEnglish
Article number214504
JournalJournal of Chemical Physics
Volume150
Issue number21
DOIs
Publication statusPublished - Jun 7 2019

Fingerprint

Ice
ice
Water
Liquids
liquids
water
decision theory
Decision theory
Dihedral angle
Coloring
Molecular dynamics
dihedral angle
Nucleation
Demonstrations
Trajectories
trajectories
nucleation
molecular dynamics

ASJC Scopus subject areas

  • Physics and Astronomy(all)
  • Physical and Theoretical Chemistry

Cite this

@article{419e68dd81744b46aef6f95a06ca5e80,
title = "A Bayesian approach for identification of ice Ih, ice Ic, high density, and low density liquid water with a torsional order parameter",
abstract = "An order parameter is proposed to classify the local structures of liquid and solid water. The order parameter, which is calculated from the O-O-O-O dihedral angles, can distinguish ice Ih, ice Ic, high density, and low density liquid water. Three coloring schemes are proposed to visualize each of the coexisting phases in a system using the order parameter on the basis of Bayesian decision theory. The schemes are applied to a molecular dynamics trajectory in which ice nucleation occurs following spontaneous liquid-liquid separation in the deeply supercooled region as a demonstration.",
author = "Masakazu Matsumoto and Takuma Yagasaki and Hideki Tanaka",
year = "2019",
month = "6",
day = "7",
doi = "10.1063/1.5096556",
language = "English",
volume = "150",
journal = "Journal of Chemical Physics",
issn = "0021-9606",
publisher = "American Institute of Physics Publising LLC",
number = "21",

}

TY - JOUR

T1 - A Bayesian approach for identification of ice Ih, ice Ic, high density, and low density liquid water with a torsional order parameter

AU - Matsumoto, Masakazu

AU - Yagasaki, Takuma

AU - Tanaka, Hideki

PY - 2019/6/7

Y1 - 2019/6/7

N2 - An order parameter is proposed to classify the local structures of liquid and solid water. The order parameter, which is calculated from the O-O-O-O dihedral angles, can distinguish ice Ih, ice Ic, high density, and low density liquid water. Three coloring schemes are proposed to visualize each of the coexisting phases in a system using the order parameter on the basis of Bayesian decision theory. The schemes are applied to a molecular dynamics trajectory in which ice nucleation occurs following spontaneous liquid-liquid separation in the deeply supercooled region as a demonstration.

AB - An order parameter is proposed to classify the local structures of liquid and solid water. The order parameter, which is calculated from the O-O-O-O dihedral angles, can distinguish ice Ih, ice Ic, high density, and low density liquid water. Three coloring schemes are proposed to visualize each of the coexisting phases in a system using the order parameter on the basis of Bayesian decision theory. The schemes are applied to a molecular dynamics trajectory in which ice nucleation occurs following spontaneous liquid-liquid separation in the deeply supercooled region as a demonstration.

UR - http://www.scopus.com/inward/record.url?scp=85066930662&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85066930662&partnerID=8YFLogxK

U2 - 10.1063/1.5096556

DO - 10.1063/1.5096556

M3 - Article

VL - 150

JO - Journal of Chemical Physics

JF - Journal of Chemical Physics

SN - 0021-9606

IS - 21

M1 - 214504

ER -